Mutating a new column based on conditions in other columns-CodePudding

I have a dataframe:

test <- data.frame(
  ID = c(1001,1002,1003, 1004),
  b_done = c('Y', 'Y', 'Y', 'Y'),
  dd_complete = c(12, 19, 0, 8),
  dd_payment = c(12,20,0,12)
)

I want to create a new column total_payment based on the following conditions:

a) if b_done == Y and dd_complete > 0, total_payment should be 5 dd_payment

b) if b_done == Y and dd_complete == 0, total_payment should be 0

The output should be like this:

test <- data.frame(
  ID = c(1001,1002,1003, 1004),
  b_done = c('Y', 'Y', 'Y', 'Y'),
  dd_complete = c(12, 19, 0, 8),
  dd_payment = c(12,20,0,12),
  total_payment = c(17, 25, 0, 17)
)

How may I do this? Thank you!

CodePudding user response：

We can use a condition in case_when to create the column

library(dplyr)
test <- test %>%
   mutate(total_payment = case_when(b_done == 'Y' & dd_complete > 0 ~
       5   dd_payment, 
   b_done == "Y" & dd_complete == 0 ~ 0))

-output

test
    ID b_done dd_complete dd_payment total_payment
1 1001      Y          12         12            17
2 1002      Y          19         20            25
3 1003      Y           0          0             0
4 1004      Y           8         12            17

Or without an ifelse or case_when

test$total_payment <- with(test, dd_payment   (b_done == "Y" & 
        dd_complete > 0) * 5)